# dart_ml

## Contents

• #### Algorithms

• ##### Classification
• K-Nearest-Neigbor In statistics, the k-nearest neighbors algorithm (k-NN) is a non-parametric classification method
• Logistic Regressor Logistic regression is a supervised learning classification algorithm generally used where we have to classify the data into two or more classes

## Example

### Import package

``````    import 'package:dart_ml/dart_ml.dart';
``````

``````    //Minimal dataset where each columns define the feature and the last row is the target class
var dataset = [
[2.7810836, 2.550537003, 0],
[1.465489372, 2.362125076, 0],
[3.396561688, 4.400293529, 0],
[1.38807019, 1.850220317, 0],
[3.06407232, 3.005305973, 0],
[7.627531214, 2.759262235, 1],
[5.332441248, 2.088626775, 1],
[6.922596716, 1.77106367, 1],
[8.675418651, -0.242068655, 1],
[7.673756466, 3.508563011, 1]
];

``````

### Using KNN algorithm

``````    var predicted = knn(dataset, dataset, 3); // (train, test, num_neighbors)
print(predicted); //{0:5} 0 is the target class and 5 is the num of neigbors of the same class that is 0
``````

### Using Logistic regression

``````    var predicted = logreg(dataset, dataset, 0.3, 100)); // (train, test, l_rate, n_epoch)
print(predicted); //0, returns the predicted class
``````

### Next Goals

• ⬜️ Regression Algorithms
• ⬜️ Neural Networks
• ⬜️ Model Evaluations
• ⬜️ Dataset tools

### Contact

If you have questions, feel free to write me on

dart_ml